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UAV Low-altitude Logistics Operation Mode and Deep Integration of Industry and Education from the Perspective of New Quality Productive Forces
DOI: https://doi.org/10.62381/E244B05
Author(s)
Xudong Li*, Hui Guo, Yongbo Yang
Affiliation(s)
Guangdong Communication Polytechnic, Guangzhou, Guangdong, China *Corresponding Author.
Abstract
Low-altitude economy is a representative of new quality productive forces, and UAV low-altitude logistics is an important field for developing low-altitude economy. Exploring the operational mode of UAV low-altitude logistics from the perspective of new quality productive forces, exploring the multi domain application scenarios of UAV logistics and the deep integration of industry and education, has important theoretical significance and practical guidance value. Firstly, the significant advantages of UAV low-altitude logistics were analyzed, and then its operation mode was discussed. The multi domain application scenarios of UAV logistics were analyzed, and the application trends and prospects of UAV low-altitude logistics were discussed. On this basis, specific strategies and implementation suggestions for the deep integration of industry and education have been proposed from multiple aspects, providing strong support for the sustainable development of the low-altitude logistics industry.
Keywords
New Quality Productive Forces; UAV; Low-altitude Logistics; Operation Mode; Deep Integration of Industry and Education
References
[1] Zhang Xiaheng. The logic, obstacles, and suggestions for empowering new quality productive forces with low-altitude economy. Contemporary Economic Management, 1-10 [2024-12-01]. http: //kns.cnki.net/kcms/detail/13.1356.F.20240827.1151.004.html. [2] Zhou Si. Analysis of the development status of freight in the logistics industry. Modern Economic Information, 2019(24): 340. [3] Xu Jianhua, Li Quan. Development, running mode and key technologies analysis of regional cargo drones. Advances in Aeronautical Science and Engineering, 2022(4): 1-10. [4] Gu Cheng. Analysis of the Main Influencing Factors of UAV Logistics. Heilongjiang Science, 2020, 11(20): 112-113. [5] Zhang Fang Zhang Honghai, Qian Xinyue, et al. Demand prediction for drones based on “last mile” distribution. Journal of Nanjing University of Aeronautics & Astronautics, 2021, 53(06): 855-862. [6]Ghelichi Zabih, Gentili Monica, Mirchandani Pitu B. Logistics for a fleet of drones for medical item delivery: A case study for Louisville, KY.Computers & Operations Research. 2021, 135: 105443. [7] Dukkanci Okan, Koberstein Achim, Kara Bahar Y. Drones for relief logistics under uncertainty after an earthquake. European Journal of Operational Research, 2023(1): 117-132. [8] Park Hyun Jung, Lin Li Min. The relationships among drone delivery service quality, consumers` attitude and usage intention: moderating effect of desire for control.The e-Business Studies, 2017(4): 153-166. [9] Leon Steven, Chen Charlie, Ratcliffe Aaron. Consumers’ perceptions of last mile drone delivery. International Journal of Logistics Research and Applications, 2023(3): 345-364. [10] Pan Nan, Chen Qiyong. Liu Haishi, et al. Task planning of UAV stocktaking tray in complex industrial storage environment. Computer Integrated Manufacturing Systems, 2021, 27(10): 2940-2949. [11] Lu Jiansha, Zhao Linbin, Tang Hongtao.Three-dimensional path planning on unmanned aerial vehicle based on radio frequency identification inventory management. Computer Integrated Manufacturing Systems, 2018, 24(12): 3129-3135. [12] Ruan Qiongyao, Li Wenda, Zhang Shanghong, et al. UAV and sfm-based volume measurement of bulk materials in storage yard of tianjin port. Water Resources and Hydropower Engineering, 2021, 52(06): 198-205. [13] Li Feng, Wei Wenxue, Sun Xuan. Method for volume measurement and calculation of asphalt aggregate based on UAV technology. Journal of Beijing University of Technology, 2022, 48(06): 580-588+597. [14] Ren Xinhui, Gou Lizhen, Wu Tong. Drone last delivery under uncertainty failure. Journal of Guangxi University (Natural Science Edition), 2022, 47(03): 732-745. [15] Dorling Kevin, Heinrichs Jordan, Messier Geoffrey G, et al. Vehicle Routing Problems for Drone Delivery.IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017(1): 70-85. [16] Zhang Liandong, Zhang Honghai, Feng Dikun. Research on task allocation of multiple logistics unmanned aerial vehicles in urban area. Aeronautical Computing Technique, 2021, 51(06): 69-73. [17] Han Peng, Zhang Bingyu. Safety route planning of UAV based on improved ant colony algorithm. China Safety Science Journal, 2021, 31(01): 24-29. [18] Xu Jianxin, Sun Wei, Ma Chao. UAV 3D path planning based on improved particle swarm optimization. Electronics Optics & Control, 2023, 30(06): 15-21+106. [19] Arafat M Y, Moh S. JRCS: Joint routing and charging strategy for logistics drones. IEEE Internet of Things Journal, 2022(21): 21751-21764. [20] Gonzalez-R Pedro L, David Canca, Jose L, et al. Truck-drone team logistics: a heuristic approach to multi-drop route planning.Transportation Research Part C:Emerging Technologies, 2020, 114: 657-680. [21] Zhang H H, Tian T, Feng O G, et al. Research on public air route network planning of urban low-altitude logistics UAVs. Sustainability, 2023(15): 12021. [22] Yi Jia, Zhang Honghai, Wang Fei, et al. An operational capacity assessment method for an urban low-altitude UAV logistics route network. Drones, 2023(9): 582. [23] Li Duwei, Li Junlei, Gan Gaifan, et al. Opportunities and challenges of low-altitude flights in air logistics. Supply Chain Management, 2024 ,5(08)47-62.
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